Noise level estimation using weak textured patches of a single noisy image

Xinhao Liu, Masayuki Tanaka, Masatoshi Okutomi

Abstract: A patch-based noise level estimation algorithm is proposed in this paper, with patches generated from a single noisy image. One can easily estimate the noise level from image patches using principal component analysis (PCA) if the image comprises only weak textured patches. The challenge for patch-based noise level estimation is how to select weak textured patches from a noisy image. As described in this paper, we propose a novel algorithm to select weak textured patches from a single noisy image based on the gradients of the patches and their statistics. Then we estimate the noise level from the selected weak textured patches using PCA. We demonstrate experimentally that the proposed noise level estimation algorithm outperforms the state-of-the-art algorithm.